title: SQL based cardiovascular ultrasound image classification.
abstract: This paper proposes a novel method to analyze and classify the cardiovascular ultrasound echocardiographic images using Naïve-Bayesian model via database OLAP-SQL. Efficient data mining algorithms based on tightly-coupled model is used to extract features. Three algorithms are proposed for classification namely Naïve-Bayesian Classifier for Discrete variables (NBCD) with SQL, NBCD with OLAP-SQL, and Naïve-Bayesian Classifier for Continuous variables (NBCC) using OLAP-SQL. The proposed model is trained with 207 patient images containing normal and abnormal categories. Out of the three proposed algorithms, a high classification accuracy of 96.59% was achieved from NBCC which is better than the earlier methods.
authors.affiliation: Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Amrita School of Engineering, Bangalore 560 004, India. snandagopalan@gmail.com
authors.forename: S
authors.initials: S
authors.lastname: Nandagopalan
authors.forename: Adiga B
authors.initials: AB
authors.lastname: Suryanarayana
authors.forename: T S B
authors.initials: TS
authors.lastname: Sudarshan
authors.forename: Dhanalakshmi
authors.initials: D
authors.lastname: Chandrashekar
authors.forename: C N
authors.initials: CN
authors.lastname: Manjunath
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016208:Databases, Factual; D019560:Echocardiography, Three-Dimensional / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009206:Myocardium / Q000473:pathology*; D010363:Pattern Recognition, Automated